Predictors of adherence to electronic self-monitoring in patients with bipolar disorder: a contactless study using Growth Mixture Models

Introduction Several studies have reported on the feasibility and impact of e-monitoring using computers, or smartphones, in patients with mental disorders, including Bipolar Disorder (BD). Despite some promising early results, concerns have been raised about the motivation and ability of patients with BD to adhere to e-monitoring, in particular when they are depressed or manic. While studies on e-monitoring have examined the role of demographic factors, such as age, gender, or socioeconomic status and use of health apps, to our knowledge, no study has examined clinical characteristics that might impact adherence with e-monitoring of patients with BD. Objectives We analyzed adherence to e-monitoring in patients with BD who participated in an ongoing e-monitoring study and evaluated whether demographic and clinical factors would predict adherence. Methods Eighty-seven participants with BD in different phases of the illness were included. Patterns of adherence for wearable use, daily and weekly self-rating scales over 15 months were analyzed to identify adherence trajectories using growth mixture models (GMM). Multinomial logistic regression models and Multiple Component Analyses were fitted to compute the effects of predictors on GMM classes. Results Adherence rates were 79.5% for the wearable; 78.5% for weekly self-ratings; and 74.6% for daily self-ratings. GMM identified three latent class subgroups: (i) participants with good adherence with the protocol; (ii) participants with partial adherence; (iii) participants with poor adherence. Women, participants with a history of suicide attempt, and those with a history of inpatient admission were more likely to belong to the group with good adherence. Conclusions Participants with higher illness burden (e.g., history of admission to hospital, history of suicide attempts) have higher adherence rates to e-monitoring. This is important because our findings debunk myths around illness burden as an obstacle to adhere to e-monitoring studies. Participants might have seen e-monitoring as a tool for better documenting symptom change and better managing their illness, thus motivating their engagement. Disclosure of Interest None Declared

Introduction: Violence against women is a violation of human rights and is part of one of the sustainable development goals. Thus, it is very important to be able to guarantee healthcare spaces from a differential approach, in which they will be developed that promote equality and will help to prevent violence. Therefore, it is necessary to analyse the social representation that future professionals will have in health, and that can affect the approach given to this phenomenon. Objectives: To analyse the social representations of violence against women in psychology students at a university in the Colombian Caribbean. Methods: The study was qualitative, exploratory and for convenience, with the application by web platform. The sample consisted of 110 psychology students from a university in the Colombian Caribbean, aged between 18 and 32 years (M=21; SD=3). The technique of free association of words and the application of semi-structured interviews were produced to identify the central and peripheral nucleus of social representation. For data analysis, the Atlas.ti version 22 software was obtained. Results: It was found that the social representation of violence against women, in its strongest association, deals with the types of physical violence, highlighting among these physical beatings, rapes, assaults and femicides. Likewise, the effects that this phenomenon generates on the mental health of the victims and its relationship with stereotypes about gender roles, in turn, the presence of problems in the judicial system, which end up causing many cases to go unpunished or re-victimize women. Conclusions: Violence against women constitutes a health problem, having professionals in this area who can understand the psychological impact, generates advantages in the development of strategies aimed at guaranteeing better care, which contributes not only to prevent this phenomenon but also to avoiding revictimization from mental health services.

Disclosure of Interest: None Declared
Bipolar Disorders 04 EPP0787 Predictors of adherence to electronic self-monitoring in patients with bipolar disorder: a contactless study using Growth Mixture Models Methods: Eighty-seven participants with BD in different phases of the illness were included. Patterns of adherence for wearable use, daily and weekly self-rating scales over 15 months were analyzed to identify adherence trajectories using growth mixture models (GMM). Multinomial logistic regression models and Multiple Component Analyses were fitted to compute the effects of predictors on GMM classes. Results: Adherence rates were 79.5% for the wearable; 78.5% for weekly self-ratings; and 74.6% for daily self-ratings. GMM identified three latent class subgroups: (i) participants with good adherence with the protocol; (ii) participants with partial adherence; (iii) participants with poor adherence. Women, participants with a history of suicide attempt, and those with a history of inpatient admission were more likely to belong to the group with good adherence. Conclusions: Participants with higher illness burden (e.g., history of admission to hospital, history of suicide attempts) have higher adherence rates to e-monitoring. This is important because our findings debunk myths around illness burden as an obstacle to adhere to e-monitoring studies. Participants might have seen e-monitoring as a tool for better documenting symptom change and better managing their illness, thus motivating their engagement.

EPP0788
Associations between long-term lithium treatment and renal, thyroid, and parathyroid function: A registerbased study Introduction: Although the effect of lithium treatment on kidney and endocrine systems has been extensively investigated, this literature, however, suffers from substantial heterogeneity and many prior studies are limited by short follow-up on just one marker of interest. Objectives: We aimed to determine the impact of long-term lithium therapy on renal, thyroid and parathyroid function within a large real-world cohort. Methods: We performed a cohort study within the Central Region of Denmark (approximately 1.3 million inhabitants). Using the Electronic Patient Record system, we identified all patients with at least one serum-lithium (se-Li) measurement in the period from January 1, 2013 to July 20, 2022, and a reference group of patients diagnosed with bipolar disorder (ICD-10: F30, F31) was matched on age, sex and creatinine level. The outcomes were renal, thyroid, and parathyroid function as indicated by all blood tests taken during follow-up measuring creatinine, estimated glomerular filtration rate (eGFR), thyroid-stimulating hormone (TSH), parathyroid hormone (PTH) and calcium. Multilevel regression analyses adjusted for age, sex, severity of the mental disorder (as indicated by the number of hospitalizations), and somatic comorbidity calculated the association between lithium treatment and development in renal, thyroid, and parathyroid function over time.
Results: A total of 4,709 lithium users (61.5% females, median age 46 years [IQR: 32-60]) and 4,027 control individuals were identified with a total follow-up period of 14,686 person-years (median = 1.7 years, range: 1-9.5). Out of the 4,709 lithium users, a total of 3,157 were incident lithium users. The final results will be shown at the 2023 EPA Congress. Conclusions: The conclusions will be presented at the congress.

EPP0789
Are there any differences in clinical and biochemical variables between bipolar patients with or without lifetime psychotic symptoms? Introduction: Bipolar Disorder (BD) is a frequent psychiatric disorder, which can be associated with high disability. Psychotic symptoms occur in more than half of bipolar patients and are associated with an unfavorable course of the disorder (Chakrabarti et al. World J Psychiatry 2022; 12(9) 1204-1232). Objectives: The aim of this study is therefore to identify clinical and biological markers able to discriminate between BD patients with (BD-PS) and without lifetime psychotic symptoms (BD-NPS) to facilitate early diagnosis and to implement a target clinical management of these patients. Methods: We recruited 665 patients consecutively hospitalized for BD at Fondazione IRCCS Policlinico (Milan) and at San Gerardo Hospital (Monza). Data were obtained through a screening of the clinical charts and blood analyses conducted during the hospitalization. Patients were assessed by psychometric scales. The two groups (BD-PS and BD-NPS) were compared by t tests for quantitative variables and χ 2 tests for qualitative ones. Variables that resulted to be significant in univariate analyses were inserted in binary logistic models with the presence of psychotic symptoms as dependent variable. Results: Among the total sample, 64.5% of patients were affected by BD-PS while 35.5% by BD-NPS. The final binary logistic regression model showed that, compared to patients with BD-NPS, those with BD-PS had a longer duration of hospitalization (p=0.007) and were more frequently hospitalized for a manic episode (p=0.001). In addition, subjects with BD-PS had a lower score on the current Global Assessment of Functioning (GAF) (t = 3.157; p = 0.002) and were more frequently males (χ² = 4.061; p = 0.044; OR = 1.399).